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ICDCS
2002
IEEE
16 years 17 days ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...
STOC
2005
ACM
135views Algorithms» more  STOC 2005»
16 years 8 months ago
On the bias of traceroute sampling: or, power-law degree distributions in regular graphs
Understanding the graph structure of the Internet is a crucial step for building accurate network models and designing efficient algorithms for Internet applications. Yet, obtaini...
Dimitris Achlioptas, Aaron Clauset, David Kempe, C...
IJAR
2006
125views more  IJAR 2006»
15 years 7 months ago
Computing best-possible bounds for the distribution of a sum of several variables is NP-hard
In many real-life situations, we know the probability distribution of two random variables x1 and x2, but we have no information about the correlation between x1 and x2; what are ...
Vladik Kreinovich, Scott Ferson
SIGMOD
2009
ACM
175views Database» more  SIGMOD 2009»
16 years 7 months ago
Ranking distributed probabilistic data
Ranking queries are essential tools to process large amounts of probabilistic data that encode exponentially many possible deterministic instances. In many applications where unce...
Feifei Li, Ke Yi, Jeffrey Jestes
PODC
2005
ACM
16 years 1 months ago
Stochastic analysis of distributed deadlock scheduling
Deadlock detection scheduling is an important, yet oft-overlooked problem that can significantly affect the overall performance of deadlock handling. An excessive initiation of ...
Shigang Chen, Yibei Ling